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Development and validation of a risk prediction model for work disability: multicohort study
Work disability affects quality of life, earnings, and opportunities to contribute to society. Work characteristics, lifestyle and sociodemographic factors have been associated with the risk of work disability, but few multifactorial algorithms exist to identify individuals at risk of future work di...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5648892/ https://www.ncbi.nlm.nih.gov/pubmed/29051618 http://dx.doi.org/10.1038/s41598-017-13892-1 |
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author | Airaksinen, Jaakko Jokela, Markus Virtanen, Marianna Oksanen, Tuula Pentti, Jaana Vahtera, Jussi Koskenvuo, Markku Kawachi, Ichiro Batty, G. David Kivimäki, Mika |
author_facet | Airaksinen, Jaakko Jokela, Markus Virtanen, Marianna Oksanen, Tuula Pentti, Jaana Vahtera, Jussi Koskenvuo, Markku Kawachi, Ichiro Batty, G. David Kivimäki, Mika |
author_sort | Airaksinen, Jaakko |
collection | PubMed |
description | Work disability affects quality of life, earnings, and opportunities to contribute to society. Work characteristics, lifestyle and sociodemographic factors have been associated with the risk of work disability, but few multifactorial algorithms exist to identify individuals at risk of future work disability. We developed and validated a parsimonious multifactorial score for the prediction of work disability using individual-level data from 65,775 public-sector employees (development cohort) and 13,527 employed adults from a general population sample (validation cohort), both linked to records of work disability. Candidate predictors for work disability included sociodemographic (3 items), health status and lifestyle (38 items), and work-related (43 items) variables. A parsimonious model, explaining > 99% of the variance of the full model, comprised 8 predictors: age, self-rated health, number of sickness absences in previous year, socioeconomic position, chronic illnesses, sleep problems, body mass index, and smoking. Discriminative ability of a score including these predictors was high: C-index 0.84 in the development and 0.83 in the validation cohort. The corresponding C-indices for a score constructed from work-related predictors (age, sex, socioeconomic position, job strain) were 0.79 and 0.78, respectively. It is possible to identify reliably individuals at high risk of work disability by using a rapidly-administered prediction score. |
format | Online Article Text |
id | pubmed-5648892 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-56488922017-10-26 Development and validation of a risk prediction model for work disability: multicohort study Airaksinen, Jaakko Jokela, Markus Virtanen, Marianna Oksanen, Tuula Pentti, Jaana Vahtera, Jussi Koskenvuo, Markku Kawachi, Ichiro Batty, G. David Kivimäki, Mika Sci Rep Article Work disability affects quality of life, earnings, and opportunities to contribute to society. Work characteristics, lifestyle and sociodemographic factors have been associated with the risk of work disability, but few multifactorial algorithms exist to identify individuals at risk of future work disability. We developed and validated a parsimonious multifactorial score for the prediction of work disability using individual-level data from 65,775 public-sector employees (development cohort) and 13,527 employed adults from a general population sample (validation cohort), both linked to records of work disability. Candidate predictors for work disability included sociodemographic (3 items), health status and lifestyle (38 items), and work-related (43 items) variables. A parsimonious model, explaining > 99% of the variance of the full model, comprised 8 predictors: age, self-rated health, number of sickness absences in previous year, socioeconomic position, chronic illnesses, sleep problems, body mass index, and smoking. Discriminative ability of a score including these predictors was high: C-index 0.84 in the development and 0.83 in the validation cohort. The corresponding C-indices for a score constructed from work-related predictors (age, sex, socioeconomic position, job strain) were 0.79 and 0.78, respectively. It is possible to identify reliably individuals at high risk of work disability by using a rapidly-administered prediction score. Nature Publishing Group UK 2017-10-19 /pmc/articles/PMC5648892/ /pubmed/29051618 http://dx.doi.org/10.1038/s41598-017-13892-1 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Airaksinen, Jaakko Jokela, Markus Virtanen, Marianna Oksanen, Tuula Pentti, Jaana Vahtera, Jussi Koskenvuo, Markku Kawachi, Ichiro Batty, G. David Kivimäki, Mika Development and validation of a risk prediction model for work disability: multicohort study |
title | Development and validation of a risk prediction model for work disability: multicohort study |
title_full | Development and validation of a risk prediction model for work disability: multicohort study |
title_fullStr | Development and validation of a risk prediction model for work disability: multicohort study |
title_full_unstemmed | Development and validation of a risk prediction model for work disability: multicohort study |
title_short | Development and validation of a risk prediction model for work disability: multicohort study |
title_sort | development and validation of a risk prediction model for work disability: multicohort study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5648892/ https://www.ncbi.nlm.nih.gov/pubmed/29051618 http://dx.doi.org/10.1038/s41598-017-13892-1 |
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